Abstract
With recent advances in camera and visual computing technology, visual surveillance is playing a significant role in wireless sensor networks (WSNs) and cyber-physical systems (CPSs). It can be used in civilian areas for traffic control and security monitoring. Deployment is an important and fundamental issue in a WSN/CPS. Many issues, such as the quality of service, energy efficiency, and lifetime, are based on the placement of sensors. Different heuristic and deterministic methods have been proposed to achieve optimal deployment. In this paper, we propose a novel algorithm, called the Quantum-inspired Tabu Search algorithm with Entanglement (QTSwE), which is based on both the Quantum-inspired Tabu Search (QTS) algorithm and quantum entanglement feature. QTSwE is applied to a deployment problem to determine the minimum number of sensors required and their locations. This paper analyzes the property of the deployment problem and calls this phenomenon dependency. It uses the concept of quantum entanglement to build the initial positions of sensors to tackle the dependency of variables. The QTS is then used to find better solutions iteratively. Moreover, we use local search to enhance the search capability of QTS and to avoid being trapped in local optima. The experiment results showed that QTSwE outperformed other deployment approaches and used the least number of sensors to satisfy the monitoring requirement and topology connectivity. With QTSwE, the performance of surveillance system deployment has improved further.
Published Version
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